AutoNation Beneish M-Score Historical Data
The historical data trend for AutoNation's Beneish M-Score can be seen below:
* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.
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AutoNation Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.68 |
-2.89 |
-2.66 |
-2.45 |
-2.20 |
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AutoNation Quarterly Data
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Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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-2.45 |
-2.54 |
-2.31 |
-2.10 |
-2.20 |
Competitive Comparison
For the Auto & Truck Dealerships subindustry, AutoNation's Beneish M-Score, along with its competitors' market caps and Beneish M-Score data, can be viewed below:
* Competitive companies are chosen from companies within the same industry, with headquarter located in same country, with closest market capitalization; x-axis shows the market cap, and y-axis shows the term value; the bigger the dot, the larger the market cap. Note that "N/A" values will not show up in the chart.
AutoNation Beneish M-Score Distribution
For the Vehicles & Parts industry and Consumer Cyclical sector, AutoNation's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where AutoNation's Beneish M-Score falls into.
AutoNation Beneish M-Score Calculation
The M-score was created by Professor Messod Beneish. Instead of measuring the bankruptcy risk (Altman Z-Score) or business trend (Piotroski F-Score), M-score can be used to detect the risk of earnings manipulation. This is the original research paper on M-score.
The M-Score Variables:
The M-score of AutoNation for today is based on a combination of the following eight different indices:
| M | = | -4.84 | + | 0.92 * DSRI | + | 0.528 * GMI | + | 0.404 * AQI | + | 0.892 * SGI | + | 0.115 * DEPI |
| = | -4.84 | + | 0.92 * 1.2131 | + | 0.528 * 1.0247 | + | 0.404 * 0.9796 | + | 0.892 * 0.9987 | + | 0.115 * 0.9685 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0765 | + | 4.679 * 0.022763 | - | 0.327 * 1.0298 |
| = | -2.20 |
* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.
| This Year (Dec23) TTM: | Last Year (Dec22) TTM: |
Total Receivables was $1,040 Mil.
Revenue was 6767.4 + 6892.7 + 6890.1 + 6398.7 = $26,949 Mil.
Gross Profit was 1215.2 + 1294.6 + 1335.3 + 1286.4 = $5,132 Mil.
Total Current Assets was $4,307 Mil.
Total Assets was $11,980 Mil.
Property, Plant and Equipment(Net PPE) was $4,184 Mil.
Depreciation, Depletion and Amortization(DDA) was $221 Mil.
Selling, General, & Admin. Expense(SGA) was $3,253 Mil.
Total Current Liabilities was $5,583 Mil.
Long-Term Debt & Capital Lease Obligation was $3,741 Mil.
Net Income was 216.2 + 243.7 + 272.5 + 288.7 = $1,021 Mil.
Non Operating Income was 19.8 + -5 + 4.4 + 5.2 = $24 Mil.
Cash Flow from Operations was -38.6 + 255.6 + -3 + 510 = $724 Mil.
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Total Receivables was $859 Mil.
Revenue was 6697 + 6666 + 6869.2 + 6752.8 = $26,985 Mil.
Gross Profit was 1281.9 + 1312.8 + 1361.7 + 1308.9 = $5,265 Mil.
Total Current Assets was $3,138 Mil.
Total Assets was $10,060 Mil.
Property, Plant and Equipment(Net PPE) was $3,931 Mil.
Depreciation, Depletion and Amortization(DDA) was $200 Mil.
Selling, General, & Admin. Expense(SGA) was $3,026 Mil.
Total Current Liabilities was $3,406 Mil.
Long-Term Debt & Capital Lease Obligation was $4,197 Mil.
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1. DSRI = Days Sales in Receivables Index
Measured as the ratio of Revenue in Total Receivables in year t to year t-1.
A large increase in DSR could be indicative of revenue inflation.
| DSRI | = | (Receivables_t / Revenue_t) | / | (Receivables_t-1 / Revenue_t-1) |
| = | (1040.4 / 26948.9) | / | (858.8 / 26985) |
| = | 0.038606 | / | 0.031825 |
| | = | 1.2131 |
2. GMI = Gross Margin Index
Measured as the ratio of gross margin in year t-1 to gross margin in year t.
Gross margin has deteriorated when this index is above 1. A firm with poorer prospects is more likely to manipulate earnings.
| GMI | = | GrossMargin_t-1 | / | GrossMargin_t |
| = | (GrossProfit_t-1 / Revenue_t-1) | / | (GrossProfit_t / Revenue_t) |
| = | (5265.3 / 26985) | / | (5131.5 / 26948.9) |
| = | 0.19512 | / | 0.190416 |
| | = | 1.0247 |
3. AQI = Asset Quality Index
AQI is the ratio of asset quality in year t to year t-1.
Asset quality is measured as the ratio of non-current assets other than Property, Plant and Equipment to Total Assets.
| AQI | = | (1 - (CurrentAssets_t + PPE_t) / TotalAssets_t) | / | (1 - (CurrentAssets_t-1 + PPE_t-1) / TotalAssets_t-1) |
| = | (1 - (4306.9 + 4183.7) / 11980) | / | (1 - (3138 + 3930.7) / 10059.7) |
| = | 0.291269 | / | 0.297325 |
| | = | 0.9796 |
4. SGI = Sales Growth Index
Ratio of Revenue in year t to sales in year t-1.
Sales growth is not itself a measure of manipulation. However, growth companies are likely to find themselves under pressure to manipulate in order to keep up appearances.
| SGI | = | Sales_t | / | Sales_t-1 |
| = | Revenue_t | / | Revenue_t-1 |
| = | 26948.9 | / | 26985 |
| | = | 0.9987 |
5. DEPI = Depreciation Index
Measured as the ratio of the rate of Depreciation, Depletion and Amortization in year t-1 to the corresponding rate in year t.
DEPI greater than 1 indicates that assets are being depreciated at a slower rate. This suggests that the firm might be revising useful asset life assumptions upwards, or adopting a new method that is income friendly.
| DEPI | = | (Depreciation_t-1 / (Depreciaton_t-1 + PPE_t-1)) | / | (Depreciation_t / (Depreciaton_t + PPE_t)) |
| = | (200.3 / (200.3 + 3930.7)) | / | (220.5 / (220.5 + 4183.7)) |
| = | 0.048487 | / | 0.050066 |
| | = | 0.9685 |
Note: If the Depreciation, Depletion and Amortization data is not available, we assume that the depreciation rate is constant and set the Depreciation Index to 1.
6. SGAI = Sales, General and Administrative expenses Index
The ratio of Selling, General, & Admin. Expense(SGA) to Sales in year t relative to year t-1.
SGA expenses index > 1 means that the company is becoming less efficient in generate sales.
| SGAI | = | (SGA_t / Sales_t) | / | (SGA_t-1 /Sales_t-1) |
| = | (3253.2 / 26948.9) | / | (3026.1 / 26985) |
| = | 0.120717 | / | 0.11214 |
| | = | 1.0765 |
7. LVGI = Leverage Index
The ratio of total debt to Total Assets in year t relative to yeat t-1.
An LVGI > 1 indicates an increase in leverage
| LVGI | = | ((LTD_t + CurrentLiabilities_t) / TotalAssets_t) | / | ((LTD_t-1 + CurrentLiabilities_t-1) / TotalAssets_t-1) |
| = | ((3740.7 + 5582.5) / 11980) | / | ((4196.7 + 3405.7) / 10059.7) |
| = | 0.77823 | / | 0.755728 |
| | = | 1.0298 |
8. TATA = Total Accruals to Total Assets
Total accruals calculated as the change in working capital accounts other than cash less depreciation.
| TATA | = | (IncomefromContinuingOperations_t | - | CashFlowsfromOperations_t) | / | TotalAssets_t |
| = | (NetIncome_t - NonOperatingIncome_t | - | CashFlowsfromOperations_t) | / | TotalAssets_t |
| = | (1021.1 - 24.4 | - | 724) | / | 11980 |
| | = | 0.022763 |
An M-Score of equal or less than -1.78 suggests that the company is unlikely to be a manipulator. An M-Score of greater than -1.78 signals that the company is likely to be a manipulator.
AutoNation has a M-score of -2.20 suggests that the company is unlikely to be a manipulator.
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